A process‐based hypothesis for the barchan–parabolic transformation and implications for dune activity modelling
Bibliographic record
Abstract
ABSTRACT The introduction of vegetation to bare barchan dunes can result in a morphological transformation to vegetated parabolic dunes. Models can mimic this planform inversion, but little is known about the specific processes and mechanisms responsible. Here we outline a minimalist, quantitative, and process‐based hypothesis to explain the barchan–parabolic transformation. The process is described in terms of variations in the stabilization of wind‐parallel cross‐sectional dune slices. We hypothesize that stabilization of individual ‘dune slices’ is the predictable result of feedbacks initiated from colonization of vegetation on the slipface, which can only occur when slipface deposition rates are less than the deposition tolerance of vegetation. Under a constant vegetation growth regime the transformation of a barchan dune into a parabolic dune is a geometric response to spanwise gradients in deposition rates. Initial vegetation colonization of barchan horns causes shear between the anchored sides and the advancing centre of the dune, which rotates the planform brinkline angle from concave‐ to convex‐downwind. This reduces slipface deposition rate and allows vegetation to expand inward from the arms to the dune centre. The planform inversion of bare barchans dunes into vegetated parabolic dunes ultimately leads to complete stabilization. Our hypothesis raises several important questions for future study: (i) are parabolic dunes transitional landforms between active and vegetation‐stabilized dune states? (ii) should stabilization modelling of parabolic dune fields be treated differently than linear dunes? and (iii) are stabilized parabolic dune fields ‘armoured’ against re‐activation? Copyright © 2012 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".